Today, audiovisual contents are transmitted via video on-demand services, video catch-up, live etc. These services possess well-defined production and broadcasting chains with which errors may appear and accumulate on the various links of these two chains.
Depending on the systems for capture, contribution, encoding, transmission, reception, and the audiovisual terminals employed, the errors may be manifested through the appearance of artifacts in the audio and video components. The appearance of these degradations may occur simultaneously in both these components.
Defects of the video component often arise through image jerk or freeze. Defects in the audio component are manifested for their part as a sound loss. The duration of these two degradations fluctuates from a few milliseconds to a few hours. The frequency of appearance of this type of event can also vary over time. The defects can equally well be of low occurrence as sustained according to a time scale.
These degradations are a source of discomfort to end users, which sometimes leads them to reject the service, if the annoyance caused becomes too significant.
Currently, the appliances deployed which ensure automatic control of audiovisual quality perform measurements on the audio and video components of signals output by the terminal or samples at the level of the decoder without taking account of the reference signal, since these latter are rendered inaccessible technically or by law. They use models classed as “reference-free” and produce scores which fluctuate over a quality scale. The conclusions of appraisals of “reference-free” prediction devices have shown that performance must be greatly improved with respect to human sentiment.
A method for evaluating a degradation in quality of an audiovisual signal based on a model for predicting the impact of the discontinuity of the fluidity of the images on subjective quality is known from document WO2006/103327. A basic scheme of the evaluation method in question is presented in conjunction with FIG. 1. Measurements of discontinuity are conducted in parallel on the video and audio components of the signal to be evaluated. Various audio and video metrics are employed to rate various types of defect (for example image freezes, the presence of blurring or else of blockiness in the images for the video component, sound losses for the audio component). A video decision module takes into account the results of the evaluations carried out with the aid of the various metrics and allots an overall quality score to the video component, with the aid of a video interaction model. An audio decision module does likewise for the audio component and allots an overall quality score to the audio component on the basis of an audio interaction model. An audio/video weighting module takes into account both the video overall quality score and the audio overall quality score so as to assign an overall quality score to the audiovisual signal. This entails a so-called cognitive approach since the model reproduces the mechanism of human judgment through the production of scores on a quality scale.
The prior art calculates the degradation in the perceived quality caused by each break in fluidity, and sound cutoff. The calculations are performed in a disjoint manner on the audio and video components and without a priori or a posteriori interaction of the results obtained. This approach fails when faced with artificially created discontinuities and when they are not considered to be perceivable by human judgment. In these typical cases, interpretation errors appear and generate false alarms.